1. Technical Field
The invention relates to analog circuits, systems and related signal processing. In particular, the invention relates to image processing using biologically inspired neuromorphic circuits and systems.
2. Description of Related Art
Complex, real-time and near real-time processing and control applications are becoming more commonplace and important. Examples include, but are not limited to, image processing, especially real-time image processing, from a large array of sensors (e.g., a focal plane array of optical sensors) that may involve simultaneous processing of multiple, parallel channels. Such image processing often presents significant design challenges including, but not limited to, providing implementations that have sufficient processing capability and at the same time exhibit reasonable energy efficiency. Neural networks, especially neural networks using neuromorphic circuits (e.g., neuromorphic neurons and synapses) and related circuit topologies, may offer a solution to some of these significant obstacles associated with the design and implementation of real-time processing and control.
For example, retino-thalamic visual processing of the output of retinal ganglion cells may provide a path to efficient image processing of real-time images. However, while neuromorphic models based on a spiking thalamus model have been developed, these models generally focus on abstract thalamocortical features including rhythms and synchrony of thalamocortical functionality associated with the image processing. In particular, existing retino-thalamus models typically fail to provide form and motion processing of images with spiking dynamics. Hence, challenges remain in developing practical implementations of neuromorphic retino-thalamic models and systems that may be applied to a wide variety of practical image processing applications which, by necessity, involve at least some form and motion processing of images.